Precision Medicine in Patients with Differential Diabetic Phenotypes: Novel Opportunities from Network Medicine

2021 ◽  
Vol 18 ◽  
Author(s):  
Claudio Napoli ◽  
Giuditta Benincasa ◽  
Samer Ellahham
Keyword(s):  
Precision Medicine ◽  
Protein Interactions ◽  
Randomized Clinical Trials ◽  
Growth Factor Receptor ◽  
Cardiovascular Complications ◽  
Personalized Therapy ◽  
Network Medicine ◽  
Prediabetic State ◽  
Relevant Role ◽  
Approved Drugs

Introduction: Diabetes mellitus (DM) comprises differential clinical phenotypes ranging from rare monogenic to common polygenic forms, such as type 1 (T1DM), type 2 (T2DM), and gestational diabetes, which are associated with cardiovascular complications. Also, the high-risk prediabetic state is rising worldwide, suggesting the urgent need for early personalized strategies to prevent and treat a hyperglycemic state. Objective: We aim to discuss the advantages and challenges of Network Medicine approaches in clarifying disease-specific molecular pathways, which may open novel ways for repurposing approved drugs to reach diabetes precision medicine and personalized therapy. Conclusion: The interactome [or protein-protein interactions (PPIs)] is a useful tool to identify subtle molecular differences between precise diabetic phenotypes and predict putative novel drugs. Despite being previously unappreciated as T2DM determinants, the growth factor receptor-bound protein 14 (GRB14), calmodulin 2 (CALM2), and protein kinase C-alpha (PRKCA) might have a relevant role in disease pathogenesis. Besides, in silico platforms have suggested that diflunisal, nabumetone, niflumic acid, and valdecoxib may be suitable for the treatment of T1DM; phenoxybenzamine and idazoxan for the treatment of T2DM by improving insulin secretion; and hydroxychloroquine reduce the risk of coronary heart disease (CHD) by counteracting inflammation. Network medicine has the potential to improve precision medicine in diabetes care and enhance personalized therapy. However, only randomized clinical trials will confirm the clinical utility of network-oriented biomarkers and drugs in the management of DM.

scholarly journals Network Medicine: A Clinical Approach for Precision Medicine and Personalized Therapy in Coronary Heart Disease

2020 ◽  
Vol 27 (4) ◽  
pp. 279-302 ◽  
Author(s):  
Teresa Infante ◽  
Luca Del Viscovo ◽  
Maria Luisa De Rimini ◽  
Sergio Padula ◽  
Pio Caso ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Precision Medicine ◽  
Personalized Therapy ◽  
Clinical Approach ◽  
Network Medicine

Repositioning Drugs for Rare Immune Diseases: Hopes and Challenges for a Precision Medicine

2018 ◽  
Vol 25 (24) ◽  
pp. 2764-2782 ◽  
Author(s):  
Erica Valencic ◽  
Alenka Smid ◽  
Ziga Jakopin ◽  
Alberto Tommasini ◽  
Irena Mlinaric-Rascan
Keyword(s):  
Precision Medicine ◽  
Rare Diseases ◽  
Business Models ◽  
Drug Repositioning ◽  
Drug Action ◽  
Primary Immunodeficiency Diseases ◽  
Computational Sciences ◽  
Approved Drugs ◽  
Molecular Mode ◽  
Viable Business

Human primary immunodeficiency diseases (PIDs) are a large group of rare diseases and are characterized by a great genetic and phenotypic heterogeneity. A large subset of PIDs is genetically defined, which has a crucial impact for the understanding of the molecular basis of disease and the development of precision medicine. <p> Discovery and development of new therapies for rare diseases has long been de-privileged due to the length and cost of the processes involved. Interest has increased due to stimulatory regulatory and supportive reimbursement environments enabling viable business models. <p> Advancements in biomedical and computational sciences enable the development of rational, designed approaches for identification of novel indications of already approved drugs allowing faster delivery of new medicines. Drug repositioning is based either on clinical analogies of diseases or on understanding of the molecular mode of drug action and mechanisms of the disease. All of these are the basis for the development of precision medicine.

scholarly journals Deciphering the interactions of SARS-CoV-2 proteins with human ion channels using machine learning-based method

2021 ◽  
Author(s):  
Nupur S. Munjal ◽  
Dikscha Sapra ◽  
Abhishek Goyal ◽  
K.T. Shreya Parthasarathi ◽  
Akhilesh Pandey ◽  
...  
Keyword(s):  
Machine Learning ◽  
Ion Channels ◽  
Protein Interactions ◽  
Transient Receptor Potential ◽  
Trp Channels ◽  
Transmission Rate ◽  
Drug Repurposing ◽  
Receptor Potential ◽  
Ppi Networks ◽  
Approved Drugs

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the worldwide COVID-19 pandemic which began in 2019. It has a high transmission rate and pathogenicity leading to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning-based algorithms are providing higher accuracy for host-SARS-CoV-2 protein-protein interactions (PPIs). In this study, predictions of PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were performed using PPI-MetaGO algorithm. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% MCC score and 84.09% F1 score. Thereafter, PPI networks of SARS-CoV-2 proteins with HICs were generated. Furthermore, biological pathway analysis of HICs interacting with SARS-CoV-2 proteins showed the involvement of six pathways, namely inflammatory mediator regulation of TRP channels, insulin secretion, renin secretion, gap junction, taste transduction and apelin signaling pathway. The inositol 1,4,5-trisphosphate receptor 1 (ITPR1) and transient receptor potential cation channel subfamily A member 1 (TRPA1) were identified as potential target proteins. Various FDA approved drugs interacting with ITPR1 and TRPA1 are also available. It is anticipated that targeting ITPR1 and TRPA1 may provide a better therapeutic management of infection caused by SARS-CoV-2. The study also reinforces the drug repurposing approach for the development of host directed antiviral drugs.

scholarly journals Discovery, development and application of drugs targeting BCL-2 pro-survival proteins in cancer

2021 ◽  
Author(s):  
Erinna F. Lee ◽  
W. Douglas Fairlie
Keyword(s):  
Structural Biology ◽  
Protein Interactions ◽  
Basic Science ◽  
Great Success ◽  
Protein Protein Interactions ◽  
New Class ◽  
Success Stories ◽  
History Of ◽  
Approved Drugs ◽  
Close Relatives

The discovery of a new class of small molecule compounds that target the BCL-2 family of anti-apoptotic proteins is one of the great success stories of basic science leading to translational outcomes in the last 30 years. The eponymous BCL-2 protein was identified over 30 years ago due to its association with cancer. However, it was the unveiling of the biochemistry and structural biology behind it and its close relatives’ mechanism(s)-of-action that provided the inspiration for what are now known as ‘BH3-mimetics’, the first clinically approved drugs designed to specifically inhibit protein–protein interactions. Herein, we chart the history of how these drugs were discovered, their evolution and application in cancer treatment.

scholarly journals Personomics – an innovative tool of precision medicine and its role in the individualized treatment of patients with breast cancer

2020 ◽  
pp. 1-8
Author(s):  
Katarzyna Rygiel
Keyword(s):  
Breast Cancer ◽  
Precision Medicine ◽  
Growth Factor Receptor ◽  
Personal Characteristics ◽  
Biological Properties ◽  
Clinical Tool ◽  
Her2 Positive ◽  
Number Of Patients ◽  
Health Related ◽  
Standard Medical Treatment

Precision medicine considers specific biological characteristics of each individual patient to tailor diagnostic and therapeutic strategies to a given patient. This approach is particularly important for a growing number of patients with malignancies. Currently, some unique biological properties in the terms of different “omics” platforms (e.g., genomics, proteomics, transcriptomics, metabolomics, epigenomics, and pharmacogenomics) have been introduced to precision medicine. In addition, specific personal characteristics of the patients have been described as personomics. It should be highlighted that personomics include an individual patient’s personality type, set of personal values, priorities, preferences, health-related beliefs, goals, economical status, and different life circumstances, which influence when and how a certain disease (e.g., breast cancer (BC)) can be manifested in a given person. As a consequence, personomics are considered to be an innovative clinical tool that is crucial for making a connection between the existing and emerging, more individualized model of medical care. This is particularly important among patients suffering from the most difficult to treat cancers (e.g., BC subtypes, such as the triple-negative BC (TNBC), and the human epidermal growth factor receptor 2 (HER2)-positive BC). This mini-review addresses some research concepts in personalized medicine, focusing on personomics, which apply individualized data of the patient to the therapeutic plan. In this light, personomics can facilitate the transition from standard medical treatment to personalized medical management of individual women with BC.

Cancer therapy-related cardiac dysfunction: is endothelial dysfunction at the heart of the matter?

2021 ◽  
Vol 135 (12) ◽  
pp. 1487-1503
Author(s):  
Crizza Ching ◽  
Dakota Gustafson ◽  
Paaladinesh Thavendiranathan ◽  
Jason E. Fish
Keyword(s):  
Cancer Therapy ◽  
Cardiac Dysfunction ◽  
Inflammatory Markers ◽  
Cancer Survival ◽  
Growth Factor Receptor ◽  
Cardiovascular Effects ◽  
Cardiovascular Complications ◽  
Cardiac Biomarkers ◽  
Cancer Therapies ◽  
The Impact

Abstract Significant improvements in cancer survival have brought to light unintended long-term adverse cardiovascular effects associated with cancer treatment. Although capable of manifesting a broad range of cardiovascular complications, cancer therapy-related cardiac dysfunction (CTRCD) remains particularly common among the mainstay anthracycline-based and human epidermal growth factor receptor-targeted therapies. Unfortunately, the early asymptomatic stages of CTRCD are difficult to detect by cardiac imaging alone, and the initiating mechanisms remain incompletely understood. More recently, circulating inflammatory markers, cardiac biomarkers, microRNAs, and extracellular vesicles (EVs) have been considered as early markers of cardiovascular injury. Concomitantly, the role of the endothelium in regulating cardiac function in the context of CTRCD is starting to be understood. In this review, we highlight the impact of breast cancer therapies on the cardiovascular system with a focus on the endothelium, and examine the status of circulating biomarkers, including inflammatory markers, cardiac biomarkers, microRNAs, and endothelial cell-derived EVs. Investigation of these emerging biomarkers may uncover mechanisms of injury, detect early stages of cardiovascular damage, and elucidate novel therapeutic approaches.

scholarly journals Overview of the BioCreative VI Precision Medicine Track: mining protein interactions and mutations for precision medicine

Database ◽  
2019 ◽  
Vol 2019 ◽  
Author(s):  
Rezarta Islamaj Doğan ◽  
Sun Kim ◽  
Andrew Chatr-aryamontri ◽  
Chih-Hsuan Wei ◽  
Donald C Comeau ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Protein Interactions

scholarly journals Structure-based prediction of ligand–protein interactions on a genome-wide scale

2017 ◽  
Vol 114 (52) ◽  
pp. 13685-13690 ◽  
Author(s):  
Howook Hwang ◽  
Fabian Dey ◽  
Donald Petrey ◽  
Barry Honig
Keyword(s):  
Binding Site ◽  
Protein Interactions ◽  
Kinase Inhibitors ◽  
Structural Information ◽  
Structural Alignment ◽  
Scoring Function ◽  
A Genome ◽  
Small Molecule Ligands ◽  
Wide Scale ◽  
Approved Drugs

We report a template-based method, LT-scanner, which scans the human proteome using protein structural alignment to identify proteins that are likely to bind ligands that are present in experimentally determined complexes. A scoring function that rapidly accounts for binding site similarities between the template and the proteins being scanned is a crucial feature of the method. The overall approach is first tested based on its ability to predict the residues on the surface of a protein that are likely to bind small-molecule ligands. The algorithm that we present, LBias, is shown to compare very favorably to existing algorithms for binding site residue prediction. LT-scanner’s performance is evaluated based on its ability to identify known targets of Food and Drug Administration (FDA)-approved drugs and it too proves to be highly effective. The specificity of the scoring function that we use is demonstrated by the ability of LT-scanner to identify the known targets of FDA-approved kinase inhibitors based on templates involving other kinases. Combining sequence with structural information further improves LT-scanner performance. The approach we describe is extendable to the more general problem of identifying binding partners of known ligands even if they do not appear in a structurally determined complex, although this will require the integration of methods that combine protein structure and chemical compound databases.

scholarly journals Transcriptome of Two Canine Prostate Cancer Cells Treated With Toceranib Phosphate Reveals Distinct Antitumor Profiles Associated With the PDGFR Pathway

2020 ◽  
Vol 7 ◽  
Author(s):  
Priscila E. Kobayashi ◽  
Patrícia F. Lainetti ◽  
Antonio F. Leis-Filho ◽  
Flávia K. Delella ◽  
Marcio Carvalho ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Growth Factor ◽  
Protein Expression ◽  
Cell Line ◽  
Cell Lines ◽  
Protein Interactions ◽  
Tyrosine Kinases ◽  
Growth Factor Receptor ◽  
Dependent Manner ◽  
Upregulated Genes

Canine prostate cancer (PC) presents a poor antitumor response, usually late diagnosis and prognosis. Toceranib phosphate (TP) is a nonspecific inhibitor of receptor tyrosine kinases (RTKs), including vascular endothelial growth factor receptor (VEGFR), platelet-derived growth factor receptor (PDGFR), and c-KIT. This study aimed to evaluate VEGFR2, PDGFR-β, and c-KIT protein expression in two established canine PC cell lines (PC1 and PC2) and the transcriptome profile of the cells after treatment with TP. Immunofluorescence (IF) analysis revealed VEGFR2 and PDGFR-β protein expression and the absence of c-KIT protein expression in both cell lines. After TP treatment, only the viability of PC1 cells decreased in a dose-dependent manner. Transcriptome and enrichment analyses of treated PC1 cells revealed 181 upregulated genes, which were related to decreased angiogenesis and cell proliferation. In addition, we found upregulated PDGFR-A, PDGFR-β, and PDGF-D expression in PC1 cells, and the upregulation of PDGFR-β was also observed in treated PC1 cells by qPCR. PC2 cells had fewer protein-protein interactions (PPIs), with 18 upregulated and 22 downregulated genes; the upregulated genes were involved in the regulation of parallel pathways and mechanisms related to proliferation, which could be associated with the resistance observed after treatment. The canine PC1 cell line but not the PC2 cell line showed decreased viability after treatment with TP, although both cell lines expressed PDGFR and VEGFR receptors. Further studies could explain the mechanism of resistance in PC2 cells and provide a basis for personalized treatment for dogs with PC.

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